The present invention relates generally to the field of imaging and materials identification, and, more particularly, to a radar for imaging a subsurface area of interest and for classifying the material composition of subsurface objects, and a method therefor. Although the present invention is subject to a wide range of applications, it is especially suited for use in a ground-penetrating radar (GPR) system radar, and will be particularly described in that connection.
GPR uses radio waves to detect buried objects in non-metallic material and can penetrate soils, rock, and man-made structures. GPR is used to map the interior of objects penetrable by radio waves, similar to the way X-rays can image the inside of a human body. It us used to discriminte metallic and nonmetallic materials, utility lines, voids, bed rock layers, rebar spacing, concrete floor thickness, and other subsurface anomalies or debris.
The depth of exploration and image definition depend on the radio frequency (RF) used. Low frequencies are used for deep geological mapping. High frequencies are used for high definition imaging.
A typical ground-pulse radar (GPR) system for investigating a subsurface area of interest is shown in FIG. 1.
The function of the transmitter 204 is to generate a known waveform of RF energy to probe the subsurface area of interest 102. This energy waveform is typically a sinusoidal pulse, 0.5 to 2.0 nanoseconds seconds in duration. Use of such a narrow pulse improves the GPR systems ability to distinguish small subsurface features while simultaneously limiting the depth to which it can probe.
The narrow pulse formed by transmitter 204 is routed to an antenna 202 where it is radiated into the subsurface area of interest 102. For ease of illustration and explanation, the subsurface area of interest 102 is shown as a multilayer system. One of ordinary skill will appreciate that the thickness of the layers can be varied as well as the shape of the layers. As the electromagnetic pulse leaves the antenna it becomes a transmitted signal 209, traveling though free air until it strikes the first surface 102. A fraction of the transmitted signal 209 passes through the first surface and a fraction is reflected in other directions away from the air-first surface interface as shown in element 210A. The process of signal transmission and reflection is repeated at each layer-layer interface as the transmitted signal 209A continues to propagate into the subsurface area of interest. At each interface the transmitted portion of the signal becomes weaker as indicated by the relative widths of signals 209B and 209C.
Layers within the subsurface area of interest are defined in terms of their electromagnetic properties such as their dielectric constant. Thus, any time two materials with different electromagnetic properties abut, there will be an interface between them that affects the transmission of a propagating RF signal.
During RF pulse transmission, an isolator 203 connects the transmitter 204 to the antenna 202. Shortly after transmission, the isolator 203 breaks this connection, making a connection between the antenna 202 and receiver 205. The function of the isolator 203 is to protect the receiver""s 205 input components from damage from the high energy output of the transmitter 204.
Using one antenna for both RF pulse transmission and reception of a reflected signal 210 is called monostatic operation. If two antennas are used, one for transmission and one for reception, the operation is called bistatic. Both systems are functionally and structurally equivalent.
The task of the receiver 205 is to capture weak reflected signals 210A-C and amplify them for subsequent processing. Following reception, the captured and amplified reflected signal are passed to a signal processor 206. The specific signal processing performed depends upon the primary application of the GPR system but would, in almost all cases, include digitization so that the received signal could be placed in a digital storage device 207.
The final GPR system component is the display unit 208, the purpose of which is to present the reflected signal in a format useful to the human operator. The display unit 208 is typically a CRT screen or computer monitor. Typically, a processing unit (not shown) will analyze the digitized reflected wave signal before displaying it.
Ground-penetrating radar works according to a pulse-echo principle of clocking the two-way time of flight of an electromagnetic pulse. This type of ground-penetrating radar is called impulse radar because an unmodulated or baseband pulse is radiated rather than the usual sinusoidal burst found in conventional radar. The pulses are a sequence of impulses; there is no carrier. There is no specific frequency associated with this radar; rather, its frequency spectrum is related by the Fourier transform of the pulse. In conventional impulse radar, the free-space radiated pulse is a Gaussian-shaped impulse about 200 picoseconds wide.
A major advantage to impulse radar is that its spectrum has frequency components located close to DC, where attenuation of the signal amplitude by the medium it traverses is the lowest. For example, for the case where the transmitted signal wave front is planar with respect to a flat surface, the propagation of a transmitted wave in a homogeneous medium along the axis perpendicular to the flat surface has its signal amplitude governed by the equation:
E=E0exe2x88x92azexe2x88x92jxcex2z,xe2x80x83xe2x80x83(1)
where E0 is the amplitude of the electric field vector in volts/meter, z is the distance along the direction of propagation in meters, and xcex1 is a frequency-dependent attenuation parameter and xcex2 is a frequency-dependent phase parameter related to the two material properties magnetic permeability (xcexc) and permittivity (∈) in Farads/meter.
Equation (1) indicates that 1) the magnitude of the electric field of the transmitted signal, E, decreases as it propagates into the homogenous medium and 2) that its pulse shape is distorted because of the nonlinear phase term, xcex2z.
While the assumptions do not hold in the strictest sense, standard practice in GPR analysis holds that they are acceptable simplifications for purposes of field use and theoretical development.
A GPR pulse propagating inside the subsurface area of interest 102 will undergo transmission and reflection events whenever it encounters an interface between different layers. The propagation impedance in free space is governed by the following equation:
Z0(space)={square root over ( )}(xcexc0/∈0)xe2x80x83xe2x80x83(2)
The propagation impedance in a material (wood) having ∈r=2 is governed by the following equation:
Zr(wood)={square root over ( )}(xcexc0/∈r∈0)=Z0(space)/{square root over ( )}(∈r)=Z0(space)/{square root over ( )}2xe2x80x83xe2x80x83(3)
The free space propagation impedance is 377 ohms and the propagation impedance of wood is 266 ohms. This difference in impedance causes a difference in the reflection magnitude at the air-wood interface.
In a one dimensional analogy to propagation along a transmission line, which can be equated to time domain reflectometry (TDR), reflections off the wood layer become equivalent to reflections from a transmission line discontinuity. The reflection coefficient, R, defined as (Yxe2x88x921)/(Y+1) where Y=Z(wood)/Z(space), can be applied to determine what fraction of the radiated pulse is returned.
For example, wood with an ∈r=2, the reflection magnitude, relative to 377 ohms, is 0.17. Thus the difference in reflection magnitude between the presence and absence of a wood layer is 0.17. If the layer were metal, the reflection would be total, or 1.0. Thus, metal is easily discerned from wood by a 5.9 times greater reflection magnitude.
The parameters which determine the amount of energy that is reflected (away from the signal""s direction of travel) and transmitted (through to the next layer) are known as reflection (R) and transmission (T) coefficients respectively. The amplitude of the reflected (Er) and transmitted (Et) electric fields, for the xe2x80x9cnthxe2x80x9d layer, can be expressed in terms of these coefficients in the following manner:
Er(n)=R(n)Ei(n),xe2x80x83xe2x80x83(4)
Et(n+1)=T(n)Ei(n),xe2x80x83xe2x80x83(5)
where Er(n) is the magnitude of the reflected electric field at the nth interface, Ei(n) is the magnitude of the electric field incident to the nth interface, and E,(n+1) is the magnitude of the electric field transmitted through to the nth layer in a multilayer system. Only the electric field is considered here because the typical GPR receiver detects and processes only voltage waveforms.
The effect of reflection and transmission events on the transmitted signal 209 can be seen in FIG. 2. As the transmitted signal 209 encounters each layer in the subsurface area of interest 102, a small portion of its energy is reflected back to the receiver 205. (Reflected signal 210 is a combination of reflected signals 210A, 210B, and 210C; temporally superimposed.) The resulting received signal 210 shows a series of peaks which denote layer-layer reflection events. Successive peaks are smaller and smaller and signify the attenuation (parameter xcex1 in equation (1)) of the transmitted signal 209 as it propagates deeper into the multiayer system and the loss of energy due to reflections.
Operation is based on emitting a pulse from a transmit antenna, waiting for a brief period of time corresponding to the round trip time of flight at the speed of light, and then opening a gate connected to a receive antenna to allow the reflected pulse to be sampled. This process is typically repeated at a 1 MHz rate, allowing approximately 10,000 receive pulses to be averaged prior to driving a signal intensity display. The high level of averaging reduces the random noise accompanying the sampled signal to such an extent that extremely low amplitude signals can be detected.
Extraction procedures can be used to quantify key characteristics of the reflected radar signal which describe features of the subsurface area under study. For example: 1) the number of peaks in a reflected signal indicates the number of layers comprising the subsurface area, 2) the ratio of reflected signal peaks (210A, 210B, and 210C) provide information regarding the dielectric constant of the different layers within the subsurface area, and 3) the time between peak values can be used to determine the thicknesses of the different layers within the subsurface area. With this information, an image of the subsurface area, including objects within the subsurface area, can be constructed and displayed
Another technique is to model mathematically the propagation and reflection of an RF pulse in a subsurface area. Such a model generates a xe2x80x9cpredictedxe2x80x9d or xe2x80x9csyntheticxe2x80x9d reflection signal. In this method, parameters such as layer thickness and dielectric constant are estimated. These estimates are then input to the model which calculates a synthetic signal. Parameter estimates are adjusted until there is a sufficiently good match between the reflected and synthetic signals. The final (model) values for layer thickness and dielectric constant are taken as the extracted measures.
Since the mid-1970s work has progressed towards the development of penetrating radars, mainly for geological purposes and applications. In order to refine the resolution of the earlier radars, increased power was applied, which then gave spurious reflections and images, complicating the analysis of the imagery received. This methodology received lukewarm support from many of other potential users.
Currently, many types of RF and seismic devices are used to provide imaging of underground structures and objects. However, existing imaging technologies suffer from expensive instrumentation, complex procedures, and poor resolution. In addition, the existing technologies degrade to incomprehensible imagery when operated in harsh environmental conditions (e.g., rain, snow, etc.).
In the area of medical imaging, there are many technologies (e.g., X-ray, MMI, MRI, CAT) using classical techniques of varying effectiveness and applications. Much of this equipment is very expensive which limits accessibility, and the imagery can be difficult to interpret. The patient, too, is often subject to very uncomfortable procedures, and, depending upon the technology, also subject to potentially hazardous side effects.
In the area of communications, existing technologies are limited in penetrating large barriers, such as mountains or oceans, or large, dense man-made structures. Relay stations, repeaters, and certainly communications satellites drive up the cost and complexity of communicationsxe2x80x94and the proliferation of such technology is continually increasing the ambient Radio Frequency Interference within the radio spectra as well as diminishing the available frequencies for new users. All these add to cost and increasing dependence on complex frequency and power management.
Many of these concerns are being addressed, but with classical approaches and indifferent results. While there have been many development efforts over the past 20 years, each has consistently displayed one or more the following functional or operational limitations: (a) limited power with very short range capabilities (e.g., proximity sensors), (b) unobserved or misunderstood capabilities to penetrate metals or sea water, (c) inability to obtain high-resolution images of deeply buried objects, (d) inability to consistently detect and discriminate targets under harsh environmental conditions (e.g., rain, snow), and (e) inability to perform discrimination of various material compositions.
A major drawback of conventional impulse radar systems is their inability to penetrate good conductors, such as sea water or metals. Using traditional theory it is considered impossible to penetrate good conductors using electromagnetic radiation. Thus, the interior of a metal-cased enclosure can not be explored and its contents identified. The ability to penetrate such enclosures can be of great benefit in detecting potentially hazardous contents of steel drums, discriminating live land mines from rocks or other clutter, discriminating spent ammunition casings from live ammunition, etc.
Recently scientists and experimenters have begun to measure the increased penetration of ultra-narrow-pulse (UNP) electromagnetic energy, surprisingly through good conductors. To date, the anomalous penetration capabilities of UNP electromagnetic waves has not been explained.
Maxwell""s equations assume steady-state transfer of energy from the electromagnetic field into material. The traditional approach to this problem has been to statistically measure overall electromagnetic properties as a function of frequency. Materials penetrated by ultranarrow impulses, however, do not follow Maxwell""s equations; consequently, the extraction procedures and model generation techniques used with conventional impulse radars do not work well to discriminate materials and image subsurface areas.
A need therefore exists for a radar, and method therefor, that predictably and controllably penetrates various kinds of materials including metals, produces images of structures or objects buried or behind barriers, and identifies the material composition of the structures or objects.
The present invention, which tends to address this need, resides in a radar and method therefor. The radar described herein provide advantages over known ground-penetrating radars in that it, among other things, (a) achieves a much longer range, (b) produces high-definition imagery of deeply buried objects, (c) penetrates metals and seawater, (d) operates under harsh environmental conditions, and (e) performs discrimination of materials.
According to the present invention, a transceiver transmits pulses with a pulse duration and amplitude constrained by the equation, d2|E|e/mxe2x89xa61 Angstrom; where d is the pulse duration in seconds, E is the pulse amplitude in volts/meter, e equals the charge of an electron in Coulombs, and m equals the mass of an electron in Kg (e/m is the charge-to-mass ratio of an electron). A processing device provides an output representing an image of a subsurface area of interest based upon the reflected wave.
In accordance with one aspect of the present invention, the processing device controls the selection of the pulse duration and amplitude to enhance the image of a subsurface area of interest.
In accordance with still another aspect of the present invention, the pulses are in the radio-frequency range or in the laser-frequency range of the frequency spectrum or are coherent electromagnetic radiation.
In further accordance with the present invention, the processing device provides an output representing an identification of the material composition of a plurality of subsurface objects based upon the reflected wave and known properties of the plurality of subsurface objects that vary as a function of the pulse duration and amplitude.
In accordance with another aspect of the present invention, the pulse duration and amplitude are controlled to enhance the identification of the material composition of a plurality of subsurface objects.
In accordance with still another aspect of the invention, the known properties include permittivity, permeability, phase shift, and delay.
Other features and advantages of the present invention will be set forth in part in the description which follows and accompanying drawings, wherein the preferred embodiments of the present invention are described and shown, and in part become apparent to those skilled in the art upon examination of the following detailed description taken in conjunction with the accompanying drawings, or may be learned by practice of the present invention. The advantages of the present invention may be realized and attained by means of the instrumentalities and combinations particularly pointed out in the appended claims.